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About Us We are seeking experts in medical image deep learning to join our team and help develop novel computationally efficient segmentation algorithms. We welcome application from individual with
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Experience in devising and developing novel machine learning algorithms Hands on experience with ROS and physical robots Excellent mathematics skills, particularly in areas relevant to robotics and AI
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analysis algorithms for the observation and interpretation of existing and new spectroscopic data of exoplanet atmospheres. Experience on cloud/haze microphysics modelling and large scale simulations is
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(e.g. nanopore-based sequencing, reverse genetics, immunoblotting, luciferase-based assays, RT-qPCR, microscopy) to study virus evolution and innate/adaptive immunity in the context of viral infection
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research in neuro-symbolic AI, with a focus on using generative AI and prompt engineering as a method to engineer knowledge graphs one can trust. This includes the design of algorithms and architectures, but
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based on the understanding that early experience shapes the way our brain is constructed. While the “ground plan” of the brain is genetically determined, it is also influenced by environmental experience
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intracellular pathogens associated with relapsing infections in later stages. The role involves applying cutting-edge microbiological and cell biological techniques, drawing on tools from genetics
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where the antibody maturation reactions occur. The laboratory uses a multi-disciplinary approach including mouse genetics, immunological assays, genetic screening and various genomics tools. A list lab
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experience: Essential criteria PhD in Biological Sciences, Molecular Biology/Genetics, Microbiology, Immunology or related discipline. Research experience in fungal pathogenesis, especially Candida. Research
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cell biology; cancer; cardiovascular; nutrition and diabetes; genetics; infection and immunology; imaging and biomedical engineering; transplantation immunology; pharmaceutical science; physiology and